The Requirements

• PhD, Master’s with 3–5 years, or Bachelor’s with 4–7 years experience in Computer Science, Biomedical Engineering, Electrical Engineering, Computational Biology, or related technical field focusing on machine learning engineering and computer vision.
• Strong proficiency with AI/ML frameworks and computer vision libraries such as PyTorch, TensorFlow, OpenCV, MONAI, Scikit-Image, torchvision, Napari, or Bio-Formats.
• Deep expertise in computer vision algorithms including CNNs, Vision Transformers, UNet, SAM/Segment Anything, and Cellpose.
• Expert knowledge of machine learning theory, image processing fundamentals, object detection, instance segmentation, and quantitative image analysis.
• Experience working with high-dimensional scientific imaging data like fluorescence/brightfield microscopy, digital pathology whole slide images, high-content screening, and multiplexed imaging.
• Experience with Kubernetes, relational and NoSQL databases, object storage, and cloud-native architectures in public clouds, ideally AWS.
• Excellent communication skills with ability to build trusted partnerships across scientific collaborators, bioimage analysts, and cross-functional teams.

Nice to Haves

• Experience with multi-modal data fusion combining scientific imaging with genomics, transcriptomics, or clinical tabular data.
• Experience working in pharma or biotech research environments.
• Experience with workflow automation, GenAI, Vision-Language Models, and/or AI agents.

What You'll Be Doing

• Design, develop, and test robust, scalable, and maintainable AI/ML scientific web applications and backend pipelines for high-throughput scientific imaging data processing and visualization.
• Build, evaluate, and fine-tune state-of-the-art computer vision and deep learning models applied to biological and clinical imaging modalities.
• Create tools to evaluate AI/ML and vision model performance, establish benchmark datasets, and quantify model quality, robustness, and drift over time.
• Develop and maintain scalable cloud infrastructures and data pipelines for large-scale multidimensional imaging datasets such as OME-TIFF, Zarr, and HDF5.
• Contribute to architectural decisions, conduct code reviews, and evolve engineering and MLOps processes for computer vision models.
• Stay current with emerging computer vision technologies and promote continuous learning, collaboration, and curiosity within the team.

Perks and Benefits

• Work in a culture that encourages personal expression, open dialogue, and genuine connections.
• Be valued, accepted, and respected for who you are, supporting both personal and professional growth.
• Contribute to impactful healthcare innovations that aim to prevent, stop, and cure diseases worldwide.
• Join a diverse team collaborating across scientific and technical disciplines to deliver life-changing healthcare solutions.